B. S. Sidhu

Protein ontology: vocabulary for protein data

These huge amounts of protein structure data make it difficult to create explanatory and predictive models that are consistent with huge volume of data. Difficulty increase when large variety of heterogeneous approaches gathers data from multiple perspectives. In order to facilitate computational processing data, it is especially critical to develop standardized structured data representation model formats for proteomics data. In this paper, we describe a protein ontology model for integrating protein databases and deduce a structured vocabulary for understanding process of protein synthesis completely. Proposed protein ontology model provides biologists and scientists with a description of sequence, structure and functions of protein and also provides interpretation of various factors on final protein structure conformation. The structured vocabulary for protein data, describing protein ontology is composed of various type definitions for protein entry details, sequence and structural information of proteins, structural domain family of protein, cellular function of protein, chemical bonds present in the protein, and external constraints deciding final protein conformation. The proposed ontology model will provide easier ways to predict and understand proteins.

Ontology-based knowledge representation for protein data

The advances in information and communication technologies coupled with increased knowledge about genes and proteins have opened new perspectives for study of protein complexes. There is a growing need to integrate the knowledge about various protein complexes for effective disease prevention mechanisms, individualized medicines and treatments and other accepts of healthcare. In this paper we propose a protein ontology that handles the following computational challenges in the area proteomics and systems biology in general: (1) it provides more accurate interpretations and associations as conclusions are based on data and semantics. (2) It makes it possible to study relationships among proteins, protein folding, behaviour of protein under various environments, and most importantly cellular function of protein. This protein ontology is a unified terminology description integrating various protein database schemas and provides a easier way to predict and understand proteins.

The protein ontology project: Structured vocabularies for proteins

The rapid generation of accessible protein data sources has generated confusion over protein data representation. The protein ontology project seeks to provide a set of structured vocabularies for protein domains that can be used to describe cellular products in any organism. The work includes modelling protein structure and experimental data. The protein ontology framework describes: (1) Protein sequence and structure information, (2) Protein folding process, (3) Cellular functions of proteins, (4) Molecular bindings internal and external to Proteins and (5) External factors affecting final protein conformation. In this paper we will also discuss the implementation strategy for the protein ontology project. The protein ontology project provides a community resource using these, vocabularies promoting the use of common protein data representation. The goal of the protein ontology project is to produce a dynamic, controlled data and query vocabulary that can be applied to all proteins even as the knowledge of protein roles in cells is accumulating and changing.

Protein Ontology Project: 2006 updates

Protein Ontology (PO) is a means of formalizing protein data and knowledge; protein ontology includes concepts or terms relevant to the domain, definitions of concepts, and defined relationships between the concepts. PO integrates protein data formats and provides a structured and unified vocabulary to represent protein synthesis concepts. PO provides integration of heterogeneous protein and biological data sources. This paper discusses the updates that happened to Protein Ontology Project since it was last presented at Data Mining 2005 Conference.

OWL, proteins and data integration

In this paper we propose an approach to integrate protein information from various data sources by defining a Protein Ontology. Protein Ontology provides the technical and scientific infrastructure and knowledge to allow description and analysis of relationships between various proteins. Protein Ontology uses relevant protein data sources of information like PDB, SCOP, and OMIM. Protein Ontology describes: Protein Sequence and Structure Information, Protein Folding Process, Cellular Functions of Proteins, Molecular Bindings internal and external to Proteins, and Constraints affecting the Final Protein Conformation. Details about Protein Ontology are available online at http://www.proteinontology.info/.